{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "#### box 箱形图: 以四分位数查看数值类型数据的分布\n",
    "- seaborn.catplot(kind='box'): figure-level\n",
    "- seaborn.boxplot(): axes-level"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "sns.set(\n",
    "    context='talk',  # paper, notebook, talk, poster\n",
    "    style='darkgrid',  # darkgrid, whitegrid, dark, white, ticks\n",
    "    palette='Set3',  # deep,muted,bright,pastel,dark,colorblind,hls,husl,cm\n",
    "    rc={\n",
    "        'figure.figsize': [8, 6]\n",
    "    }\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "df1 = pd.read_csv('./input/athlete_events.csv')\n",
    "df2 = pd.read_csv('./input/noc_regions.csv')\n",
    "df = pd.merge(\n",
    "    df1, df2,\n",
    "    on='NOC',\n",
    "    how='left',\n",
    "    validate='m:1')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\nInt64Index: 148480 entries, 0 to 271115\nData columns (total 17 columns):\nID        148480 non-null int64\nName      148480 non-null object\nSex       148480 non-null object\nAge       148095 non-null float64\nHeight    140921 non-null float64\nWeight    140486 non-null float64\nTeam      148480 non-null object\nNOC       148480 non-null object\nGames     148480 non-null object\nYear      148480 non-null int64\nSeason    148480 non-null object\nCity      148480 non-null object\nSport     148480 non-null object\nEvent     148480 non-null object\nMedal     20324 non-null object\nregion    148199 non-null object\nnotes     2228 non-null object\ndtypes: float64(3), int64(2), object(12)\nmemory usage: 20.4+ MB\n"
     ],
     "output_type": "stream"
    }
   ],
   "source": [
    "df = df.query(\"Year>=1984\")\n",
    "df.info()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "['USA', 'CAN', 'GER', 'ITA', 'FRA', 'CHN']"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 5
    }
   ],
   "source": [
    "# （最多人参加的条目数）取前五名,再把中国加上去\n",
    "# ['USA', 'CAN', 'GER', 'ITA', 'FRA', 'CHN']\n",
    "li = df['NOC'].value_counts().head(5).index.tolist() + ['CHN']\n",
    "li"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "name": "stdout",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\nInt64Index: 36686 entries, 0 to 271037\nData columns (total 17 columns):\nID        36686 non-null int64\nName      36686 non-null object\nSex       36686 non-null object\nAge       36672 non-null float64\nHeight    36172 non-null float64\nWeight    36066 non-null float64\nTeam      36686 non-null object\nNOC       36686 non-null object\nGames     36686 non-null object\nYear      36686 non-null int64\nSeason    36686 non-null object\nCity      36686 non-null object\nSport     36686 non-null object\nEvent     36686 non-null object\nMedal     7262 non-null object\nregion    36686 non-null object\nnotes     0 non-null object\ndtypes: float64(3), int64(2), object(12)\nmemory usage: 5.0+ MB\n"
     ],
     "output_type": "stream"
    }
   ],
   "source": [
    "df = df[df['NOC'].isin(li)]\n",
    "df.info()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x25180a8f898>"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 7
    },
    {
     "data": {
      "text/plain": "<Figure size 576x432 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(\n",
    "    x='NOC',\n",
    "    y='Age', # 年龄身高和体重进行箱型图分析\n",
    "    hue='Sex', # 对比一下性别的不同\n",
    "    data=df\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x25180bfea58>"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 8
    },
    {
     "data": {
      "text/plain": "<Figure size 576x432 with 1 Axes>",
      "image/png": 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sW1i6dAFu384SOxTJql7hspWKl0zmgPr1G8DXNwCurvWs8kPt5s0buHjxvPpPqjsay+VO8PDwRv36/lqWk5sXKxNWEhbWEfv27VRn/SEhYWKHJEncAVN/9rZboSWlpHyCkpIS7N79CaZMmSl2OJLk6ekFX18/3Lt3F76+/jY3D8fZ2RXOzq5WeayNGzegpORxdcLFxQXdukVZ5bGlipUJK1JVJ1iV0C0j45yg/csvGSJFIm3VdytkdUK3rKxbuHfvLgDg3r07rE7okJ+fhwcPHgAAcnKy+ZqqgZ+f8ESN/v4NdRxZdzCZsKKwsI5ISFjGqkQN9u3bKWinpCSLFIm0cbdC/aWkfCJo7979iY4j67bK1xBfU/q4dUs4rHHz5p8iRSIdTCasiDs71o6rXvTD3Qr1p6pKPG5Lb6KcFPA1RaZgMmFF3NmxdtUnT3HVi3bcAVN/3H1WP6Gh4dXafE2R/phMWAl3dtTPs88OFrSff36ISJFIG3fA1B93n9VP9cnO3AFTt4iIpwXtbt16iBSJdDCZsBLu7Kife/eEk+OysjhZThtPTy+0bt0OQOXpyG1t5r01cfdZ/aSlnRYkqLayA6YYrl37Q9D+449LIkUiHUwmSFJsdRc+Mdy+fUvwX9KO83D0k5mZLpjUy/eebpyHo4nJBElKq1ZPCtpBQa1FikTasrJu4cGDbABAdvZ9LnesAefh6IfzcPTHeTiamExYCXd21M/du7cF7Tt3+CWpDZc76o+7z+qnct4N5+HoIzb2b4L2iy/+TceRdQeTCSuJjOwmaHNnR+2ys+/X2KZKLLPqLyyso6DNfV60q9wB0xcA4OPjx3k4NWjcuImg3ahRY5EikQ4mE1aSn5+nPvmMg4MDd5fTwdHRqcY2VfLyEp60x9u7vkiRSF9+fh4cHB6X7/ne065yB8zKobMHD+6zn2rw+ef7BO2vvtovUiTSwWTCSlJTD8PB4XEJkbvLaVdeXlZjmyo9evRI0C4uLhYpEulLTT2Mquc44ntPu+r9wn7S7cyZ7wXtU6dOihSJdDCZsBLuLkfmVFpaUmObHuN7Tz/sJzIFkwkr4UxpMidXV9dqbTeRIpE+7uyon9DQcME+E+wnMgSTCTNSKBTIyXmg9S88vIv6OJlMhvDwzhrH1KX177r6qmXLIMFxrVoF1+l+0iUubpSgPXz4KB1HUosWrQTtwMBWOo6s27p0iRTsM8EdMHVr3LiZoN2sWQuRIpEOR7EDsBcKhQLr1q1GTk52rceWl5cjMXGDxuU+Pn6YOnWWWdfB5+fnYdeujxEXN1Iys7MN6avLly9h7doVgsss0U+2Jjj4STg5OaOsrBTOzs5o1SpY7JAk68svhbvN7t+/hys6tKi+xf+ZM6cxaNAwHUfXbVlZwrOG3rhxXaRIpIOVCTuXmnoY169f5WQqu/T4VyTpVn2y6qNHnKyqDXefJVOwMmEmcrkcU6fOQl5ertbr8/JykZT0IQBg3LjJGkv7gMrlfuauSqSnp0GpVCI9/QyioqIlUZ2oqa/E6CdbdOnS7ygrq1zpUlZWhsuXL7E6oYOLiwtKSkoEbdLUvHlLXLr0q7r9xBOBIkZDtobJhBnJ5XL4+PjWepyXl7dex5kqNfWwYAw0NfWwZMqW+vSVtfrJFu3atV3Q3rlzO+LjF4gUjbTxS1I/f/55VdC+du2KOIHYALlcLpi7Vdd/3AAc5rBrXOplv1i61x+/JPVTtXqjrU2P8eRxmliZsGNt24bg3LmfqrQ7iBgNmRNL9/rz9fVHVtZNddvfv4GI0YhPoVBoHWLU9prKyXmgcVxdGWbU1U+Afn1VV/pJhcmEHdOcmMeJevaCpXv9VU0kAODmzRs6jrR/hqykKikp0VhJBdSN1VSG9BOgva/qQj9VxWEOO/brr+cF7YsXfxEpEjI3lu6JSEpYmbBjjRs3w9Wrf6jbTZs2FzEaMoauUmvr1u0ES/natGlXp0vSQM1l6erqakla35VUzz47CO3atdd6H3WhrwxZnaerr+pCP1XFZMKOXb8u/LV69eplkSIhYxhSas3ISEdGRrrG5XWl1GpoWboul6T1WUnVrl37Or+SSt/VeeyrShzmsGMVFRU1tkno0qXf8c47c3H58iWxQyEisimsTNgxroU2zK5d26FUKiWzZ4O+JekRI0ajUaPGWu+jrpRa9e2rLl0i0bNnlMYxdaWfiCyFyYQdGzp0OFJSPla3Y2NHiBiNtF269Lt674ZHj4ols6OkPqXWRo0as8wK/fqqZ88o9hWRBXCYw46FhXUUnPacJzfSTduOkkREpB8mE3Zu6NDhAFiVqA13lCQiMh6HOexcWFhHhIV1FDsMyXN1dRUkFK6ubiJGQ0RkW1iZsHP5+XlISvoQ+fn5YociaXFxowTt4cNH6TiSSH8HD36FhIR4HDlyUOxQiCyKyYSdS009jOvXryI19bDYoUhacPCTgvklUph8Sbbvu++OAQC+/faImGEQWZyoyURFRQU+/vhjDB48GJ06dUK/fv2wdOlSFBQUqI/JzMzE6NGj0alTJ/Ts2ROrV69GWVmZ4H6uXr2K1157DREREYiMjMSCBQsE91FX5efnIT09DUqlEunpZ1idqEF+fl61NvuKTHPw4FeCNqsTZM9ETSYSExOxaNEi9O7dG+vXr8e4ceOwd+9ezJgxAwBw7do1jB07Fi4uLlizZg3Gjx+PpKQkLF26VH0fubm5GDNmDO7fv4/ly5fj9ddfx5dffonXX39drKclGamph9Un+1IqlaxO1KB637CvyFTffXdM0GZ1guyZaBMwlUolEhMTMWLECPUXf/fu3eHj44OZM2fiwoUL+Oijj+Dp6YkNGzbA2dkZUVFRcHV1xeLFizF58mQEBARg+/btyMvLw969e+Hj4wMACAgIwKRJk3Du3Dl07Fh3Jx9mZqarN61SKBTIzDyLQYOGiRyVNLGviIiMJ1plorCwEEOGDMGgQYMEl7dq1QoAcP36dZw8eRJ9+vSBs7Oz+vr+/ftDoVDgxIkTAICTJ0/iqaeeUicSANCzZ0+4u7sjNTXVCs9EukJDwwXzAEJDO4kckXSFhoZXa7OviIj0JVoy4eHhgfnz56NLly6Cyw8dOgQACAoKQlZWFgIDAwXX+/r6wsPDA1euVJ7E6vLlyxrHyOVyNGvWTH1MXRUVFQ2ZTAYAkMlkiIqKFjki6WrRopWgHRjYSseRRPrp3r23oN2rV19xAiGyAkntM3Hu3Dls3LgR/fr1g5eXF4DKpKM6d3d39QTL/Pz8Wo8xlEwGeHubd58BhcJV/W8vL1ez37823t5uiIyMxHfffYfIyEg0a9bQ4o9pKjH6CQAOHNgraH/++R507x5plcc2hlj9ZIvE6quXXnpBMG/ihReGWuVxjcXXlP7ssa/++t1pNMksDU1LS8PEiRPRrFkzLF68WD1xUKblGSqVSjg4PA5dn2PqqpiY59CqVSs8+2x/sUORtOLi4hrbRMbo06eyGhgTEyNyJESWJYnKxJdffon4+Hi0bNkSiYmJ8PHxQWFhIQBorS4UFRXB09MTQGXlQtsxhYWFaNq0qVHxKJVAbq55v0zy8h4J/i2XW+vLyhmjR79qkedkCWL1k7YdMKXcX+K9nmyPmH0VFRWDqKjKRELKryeArylD2GNf+fl5mFSdEP2ne1JSEmbNmoXw8HBs374dDRtWluLd3d0REBCAa9euCY7Pzs5GQUGBep5EYGCgxjEKhQI3btzQmEtRF3EHTP1wB0wi8Vy69DveeWcuLl++JHYoZCRRk4lPP/0Uy5Ytw4ABA5CYmKiuNqj06NEDR48eRWlpqfqyr7/+GnK5HF27dlUfc/r0aTx8+FB9zIkTJ1BUVITu3btb54lIGHfA1E9w8JOCNnfAJLKeXbu2Q6lU8my9Nky0ZCI7OxtLlixB06ZNMWrUKJw/fx7p6enqvwcPHmDixIm4d+8eJk2ahKNHj6o3rBo+fDiaNGkCABg5ciScnZ0xduxYfPPNN/j000/xxhtvoFevXujcubNYT08SuAOm/i5d+l3Q5i8kIuu4dOl39RDjo0fFfO/ZKNGSiePHj6O4uBg3b97EqFGjMGLECMHf8ePHERQUhE2bNqGoqAjTp09HUlISxo0bh3nz5qnvx9fXF1u3bkX9+vUxe/ZsvP/+++jfvz/ef/99sZ6aZHAHTP3t2iX8RcRfSETWwfeefRBtAuawYcMwbFjtOwxGRERg586dNR7TunVrbN682UyR2Q/u6qi/qpMvK9u2P6HKUvLz87Br18eIixupMTRJZCi+9+yD6BMwyXK4A6b+XF1dq7Vtf924pXAeDpkT33v2gcmEHeMOmPrjag79cB4Omdvzz78gaA8e/IKOI0nKmEzYMU9PLwQGVq5KCAp6kiXpGgQHPwlHx8pRP0dHJ67m0IHzcMjcrl+/LGhfuXJZx5Ek5aX+TCbs3PXrlecnuXq1bp+nRB8KRQUAoKJCIXIk0qVtHg6RKTIz06u1+ZrSRcpDjEwm7NilS7+jpKQEAFBS8ohLrmqQkXEOSqUqmajAL79kiByRNHEeDplbmzbtBe22bUNEikTapD7EyGTCjnHJlf727ROuGEpJSRYpEmmrPu+G83BqlpFxDgkJ8UxOa6B5biUTzzhlp6Q+xMhkwo5xyZX+VKV7XW2q5OnpBV9fPwCAr68/5+HUQpWkMjnV7eLFX6q1fxYpEmmT+hAjkwk7Vv2sqTyLKpkqPz8PDx48AADk5GRLrtQqJRkZ5wQf/qxOaMehM/1IvZ/47WLHKioqamwTGaqytCrdUquUcOhMP1zCrp+oqGhBciq1fmIyQUR6k3qpVUo4dKYfT08vhId3gUwmQ3h4BIfOdPD09KrWllY/MZkgIr1JvdQqJap+0tWmx6KiotGiRUvJ/dqWktOnTwnaaWmnRYpEOyYTdszZ2UXQdnFx0XEkDRggPGcJd+HTjiVp/Q0dOlzQjo0dIVIk0ufp6YVx4yZL7te2lBw4sFfQ3r9/j0iRaMdkwo6VlpYI2qo9J0hTZGQ3QbtLl0iRIpE2T08vPPlkWwBA69bt+OFfg7CwjoJ2SEiYSJFIn5R3diT9MJmwYw0aNKzWDhApEtugqk6wKlGzu3dvAwDu3MkSORKyF1Le2ZH0I9opyMl8FAoF8vJyNS6PiRmAHTu2CNo5OQ80jvPy8q4z47m6+goAgoODMW3abDg4ONT5ftIlK+sWsrPvAwCys+/j9u0sNGrUWOSopEnbGDcrXpqq7+wYFRXNipcW3bv3xnffHVO3e/XqK1YoWjGZsHEKhQLr1q1GTk52rcfu2LFZ6+U+Pn6YOnWW3X9RGtJX2tSVfqpJSsongvbu3Z9gypSZIkUjbdrGuJlMaNK2s+OgQcNquVXd8/vv5wXtCxd+Qd++z4oUjSYOcxCR3u7du1utfUekSMhecLmxfqT+3mNlwsbJ5XJMnTpLa+k+Ly8XSUkfAgDGjZsMLy9vrfdRV8r3pvZVXemnmnh4eKKg4PEkuepr34kM1bZtCM6d+6lKu4OI0YhP11Csr68fHjx4XFX18/OT1HAskwk7IJfL4ePjW+MxXl7etR5TF7CvTFNUVChoFxYWiBSJ9MnlcsFGVXI5P261UQ1xVLlElDikwJCh2OzsbKxdu0LjcrGGYznMQUR64xbt+tPcAbNcpEik7ddfhXMBqp/4i2wDU2Ui0puDg4MggeDJ43RzdXUVnLnX1dVNxGikKyioNc6fz6zSbiNiNOLSdyh2yJA4BAa20nofHOYgIsmrV89dMGfC3d1DxGikLS5uFD766H/q9vDho0SMRrpu374laN+5c0vHkXWDPkOxgYGtJDcUy58VRKS3qokEULlHAGkXHPwkHB0rf685OjqiVatgkSOSpqqTCgGo9zEh28Jkgoj0xl1VDaNQVA4JcW6JbnxN2QcmE0SkQaFQICfngcZfTMwAwXGqXVWr/vFU25UyMs5BqXycTPzyS4bIEYmLryn7xjkTRCRg6q6q3Cm00r59OwXtlJTkOnuyL76m7B8rE0REFqC5NJS/rsl+sTJBRALcKdQ8uIz2MSm+pmo66V9tqt7O2Puwt/cJkwki0sCdQk33xBOtcOXKJXU7MDBIxGjEJ7XXVF5ertYdJA2lSoQMNWPGHLu5eUmKAAAgAElEQVR6/9TdVJmIyIJu3fpT0L5x47pIkRBZHisTZHZilw8B+yshkjTV9Fpv3bodfv75HJRKJWQyGdq0aadxYia+TqUhcEBfONWrZ9BtlH8NYckMGL4qKyrClQNHDHocW8FkgsxO7PIhYH8lRJIeQ1YoKJVKZGSkIyMjXXA5VylIg1O9enD2dBc7DJtm8DDHrVu3BPvNV5eXl4cff/zRpKCIiIjIdhhcmYiOjsZ7772HQYMGab3+4MGDWLJkCc6ePWtycGT7rFU+BOy7hEjSU9MKBUC4SmHEiNFo1KixxjFSWqXAIUYyRa3JxM2bN7Fnzx51W6lU4uDBg7h69arGsUqlEkeOHIGLi4tZgyTbxfIh2TN9VigAQKNGjW1qlQKHGMlQtSYTTZo0QWpqKjIzK08RK5PJcPDgQRw8eFDr8Q4ODpg5c6Z5oyQiIiLJqjWZkMlkSEpKQm5uLpRKJfr164c333wT0dHRGsfK5XLUr18frq6uFgmWiIj0Z+gwI4cYyVh6zZnw8PCAh4cHAGDr1q0ICgqCn5+fRQMjqgs4vq0fsZcb20o/VcdhRrIWgydgdu3aFQBQVlaGhw8foqysTOtxTZo0MS0yojqA49v6EXu5sa30E5FYDE4mcnNzMW/ePKSmpqK8vFzncRcuXDApMCIiIrINBicTy5Ytw6FDhxAZGYnQ0NA6NT+CpVayJI5v64e7FRJJj8HJxJEjR/DCCy9g6dKllohH0lhqJUvi+LZ+2E9E0mPwDpilpaXo3LmzJWIhIiIiG2RwZSIyMhKnT5/GSy+9ZIl4bAZLrURERJVqTSZu3bolaI8ZMwb//Oc/sXTpUgwcOBC+vr5w0PLlaO+rOVhqJSIiqlRrMtG3b1/IZDLBZUqlElu2bMHWrVt13o6rOYiIiOqGWpOJKVOmaCQTRERERCq1JhPTpk2zRhxkp8oKi+zysYjIfljrs8OeP6MMnoBZfQ5FdTKZDM7Ozqhfvz73RKijFAqF+t9XvhJn8mjVGIiIqhP7c8rePqMMTia0zaHQRi6Xo127dpg5cya6d+9uVHBEREQkfQYnEwsXLsSqVatQVlaGIUOGoFWrVnBxccHVq1fx+eefo6CgACNHjsSjR49w9OhRTJo0CZs3b0ZERIQl4icJqlqRCuzfF07uhi2hNVZZYZH6FwarYkRUEzE+p+z5M8rgZOK3335DvXr1kJycjIYNGwque+211/DSSy+hoqICb731FmbPno1Ro0Zhw4YN2LRpk9mCJtvh5M4ltEQkbfycMp3BO2B+/vnnGDlypEYiAQDe3t4YMWIE9u7dCwBwc3PD0KFD8fPPP5seKREREUmSwcmEQqFAxV87OWpTVlaGR48eqdsuLi41Hq9y4cIFhISE4Pbt24LLv/76awwbNgzh4eF47rnnsHnzZo37y8zMxOjRo9GpUyf07NkTq1ev1nlqdCIiIjIvg5OJiIgIbNmyBVeuXNG47ubNm9i2bZvg3B2HDx9Gq1atarzPy5cvY/LkyRqnND9x4gSmT5+ONm3aYMOGDRg2bBiWL18uGDK5du0axo4dCxcXF6xZswbjx49HUlJSnTwRGRERkRgMnjMxZ84cvPzyyxg8eDB69eqFJ554As7Ozrh69Sq+/fZbODo6Ys6cOQCAgQMH4vLly3jvvfe03ld5eTmSk5OxatUqODk5aVy/Z88etGjRAkuXLoWDgwO6d++OK1euYMeOHZg4cSIAYOPGjfD09MSGDRvg7OyMqKgouLq6YvHixZg8eTICAgIMfYpERERkAIMrE4GBgdizZw+GDBmCtLQ0JCUl4cMPP8Tx48cRHR2NlJQUtGnTBg8ePICvry8WLlyIQYMGab2vtLQ0rFy5EuPHj8fs2bM1ri8pKYGbm5vg3B/169fHw4cP1e2TJ0+iT58+cHZ2Vl/Wv39/KBQKnDhxwtCnR0RERAYyuDIBAI0bN8a7774LAHj48CHKy8vh5+cn2H/C19cX27Ztq/F+goKCcOjQIfj5+SElJUXj+lGjRuHVV1/Ftm3bMGzYMPz8889ISUnB0KFDAQDFxcXIyspCYGCg4Ha+vr7w8PDQOhRDJFXchU8/7Cf9sa/IWoxKJqqqX7++0bf19/ev8fpu3bph/PjxWLx4MRYvXgwA6NGjB+bOnQsAyM/PBwB4eHho3Nbd3R0FBQVGxSWTAd7ebhqXKxSuRt2fuXh5uWqNS5eq8Rp6W1OI3U+A7fRVaenj4T0xduFzd3diP+nB0H4C2Ff6qqufU1L7jDL1FFy1JhPt2rXDihUrMHjwYABA27Zta90BUyaT4fz586ZFBmDBggVISUnB1KlTERkZiUuXLuE///kPZsyYgQ0bNkCpVKofrzqlUqn11OhERERkXrUmE8OGDUOLFi0EbWucRfTOnTvYuXMnpkyZoj7ZWNeuXdGiRQtMmDABx44dQ9euXQFAawWiqKgInp6eRj22Ugnk5hZrXJ6X90jL0daTl/cIcrlmXDUdb+xtTSF2P6lisIW+Kix8vIRZjF34CgvL4OzMftLGlH4C2Ff6qqufU1L7jPLz8zCpOlFrMlF9ieWyZcuMfzQD3Lp1C0qlUrDMFACeeuopAMDvv/+OPn36ICAgANeuXRMck52djYKCAo25FERSxl349MN+0h/7iqzF6HGA8vJynD17Fl9++SXu37+PgoIC5Obmmi2wJ554AnK5HD/++KPg8rNnzwIAmjVrBqByDsXRo0dRWlqqPubrr7+GXC5XVy6IiIjIcoyagHngwAEsWbIE2dnZAIBNmzahtLQUM2bMwNSpU9V7QJjC19cXr7zyChITE+Hg4IDIyEhcuXIFH3zwAdq2bYt+/foBACZOnIgvvvgCkyZNwpgxY3D16lWsXr0aw4cPR5MmTUyOQxfOkiYisg9lRYZ/zir/2olZZsDcPGMex1YYnEycOHECr7/+Ojp37oyJEyeqhz2aNWuG1q1bY9WqVWjQoIF6+aYp4uPj0ahRIyQnJ2Pjxo1o1KgRBg4ciOnTp6v3lQgKCsKmTZuwYsUKTJ8+HT4+Phg3bpx6noU5VT3/vBizpKs+PhERmceVA9b/PLc3BicT69evR4cOHbB161bk5uaqk4mgoCDs2LEDf//737FlyxaDk4nY2FjExsYKLnNwcMD48eMxfvz4Gm8bERGBnTt3GvZEiIiIyCwMTiYuXLiAmTNnal126ejoiEGDBuncPtvWVT3/vBizpKs+PhERGc/LyxszZswx6rZ5eblISvoQADBu3GR4eXkb9fj2xOBkwsnJSeOEXFU9fPhQ63k27A1nSRMR2S65XA4fH1+T78fLy9ug+1EoFMjLy0VenmELFqoeb+htq/Ly8rbID1ODk4muXbti165deOWVVzSuu3v3Lnbs2IEuXbqYJTgiIiJ7kpeXi7VrV5h0H6qqiDFmzJhjliSqOoOTiVmzZmHEiBEYMmQIevXqBZlMhsOHD+PYsWPYs2cPSktLMX36dLMHSkRERNJkcDIRFBSE7du3Y/HixeoTeX300UcAgA4dOmD+/Plo166deaMkIiKyM1Om9DLw/ByVy1HlcsO2iMrNLcb69d8adBtDGbXPRJs2bbBt2zY8fPgQ169fR0VFBZo2bYoGDRqYOz4iIiK75O3tBl9f+5h7V2syoTpDpyFkMpn6FOVERERk32pNJvbs2aP1cplMpj5rp7brmEyYny3O/rXWznIAUFrlhG9i9JWlZkkTGcvQ95+x7z173tmR9FNrMnH48GGNy3JzcxEbG4uVK1eiU6dOFgmMNJkyg1es2b9i7SwnRl9ZapY0kbG4syNZS63JRNOmTTUuq1evcrMmPz8/rdcTERFR3WHUBEwSjy3M/hVrZ7mqtzW0nwDj+sqcs6TFKElz6My8jyMFxr7/THnvVVRUoKAgX/3vnJwHBj2utn8bisOM4mIyYWNsYfavWDvLVWUL/VSdGCVpDp3ZH3O8/wx97+XkPDDp9aAixc2YSD+G/aQhIiIiqoaVCSIRiVGSrn57Dp3p9/ikH2sNMQLW2YyJ9FNrMvHjjz9qXJafXzk29uuvv8LRUftdPPXUUyaGRmT/xChJV2cLQ0K2dlImoO4uN7aF1xOZX63JxOjRoyGTybRet3z5cp23u3DhgvFRERFJgDlOygRwuTHZv1qTiSlTpuhMJoiIiIhqTSamTZtmjTiIiCTNFpcbE1kLJ2ASEemBcwGIdOPSUCIiIjIJKxNEREQiePiw2G4eh8kEERGRlSgUCvW/N2yw/tyYqo9vThzmICIiIpOwMmEknmxI2uypfEhE9qPqJmT//Gcv1K9v2AohYzx8WKyuglhqEzQmE0biyYakx17Lh0Rkn+rXt58VQhzmICIiIpOwMmEAsU42VPW2pJu9lg+JiKSOyYQBxDrZUFWcC6AfeyofEhFJHZMJG8C5AEREJGWcM0FEREQmYWXCBnAuAFkSh870w37SjzXjt/W+sidMJmwM5wKQOXDoTD/sJ/2I3U/VYyDr4zAHERERmYSVCaI6iENn+mE/6UeMfgJss6/sFZMJojqOQ2f6YT/ph/1UN3GYg4iIiEzCZIKIiIhMwmEOIiIiEeTmGra0VaGoPPO0XG5YHcDQxzEGkwkiIiIRrF8vzjJaS+AwBxEREZmElQkiIiIrMfbs06acebr641sCkwkiIiIrMcfZp00587SlcJiDiIiITMJkgoiIiEzCZIKIiIhMwmSCiIiITMJkgoiIiEzC1Rw2xp52TLMkY+I3pq9svZ8Avqb0xdeUfqzVT8Y+FlkGkwkbY087plkS+0l/7Cv9sJ/0w36qmzjMQURERCZhZcIG2OuOaeZmbD8B5ukrW+kngK8pffE1pR+x+0kVgzkpFArk5eVqva7q5bqO8fLyhlwuN2tMUsZkwgbY645p5maOfgLYV/piP+nP3vvK3vpJoVBg3brVyMnJrvVYVSJUnY+PH6ZOnVVnEgrJDHNcuHABISEhuH37tuDyX3/9FRMmTECnTp3w9NNP44033sD9+/cFx2RmZmL06NHo1KkTevbsidWrV6OsrMya4RMREdVZkqhMXL58GZMnT0Z5ebng8j///BOjRo1Cu3btsGbNGjx8+BCrVq3ClClTkJycDAC4du0axo4di06dOmHNmjX4448/8P7776OgoABvv/22GE+HiIhsmFwux9Sps3QOYQBARUXlChQHB+2/yTnMYUXl5eVITk7GqlWr4OTkpHH9unXr4Ovri8TERLi4uAAAPD098c477+DPP/9E8+bNsXHjRnh6emLDhg1wdnZGVFQUXF1dsXjxYkyePBkBAQHWflpERGTjahu6eeedN6FUVsDBQY63315ixcikSdRhjrS0NKxcuRLjx4/H7NmzBdcplUocOnQIcXFx6kQCAPr27YvU1FQ0b94cAHDy5En06dMHzs7O6mP69+8PhUKBEydOWOeJEBFRnaJUVlYmKioUIkciDaImE0FBQTh06BCmTp2qUQ66ceMGCgoK0KhRI7z99tuIiIhAx44dMWvWLOTk5AAAiouLkZWVhcDAQMFtfX194eHhgStXrljtuRCRuBQKBXJyHmj8VZ95r+0YhYJfCKS/d955U9BeuHCeSJFIh6jDHP7+/jqvUyUMK1asQJcuXbB27VrcunULK1euxPTp07Ft2zbk5+cDADw8PDRu7+7ujoKCAqPikskAb283o26ri0Lhqv63l5er2e9fKo9pKrFitrW+Yj8JKRQKLFv2rsbk7Op0zbz39/dHfPybZh3jlmpf6cLXlP5UVQmVigqFxeO2dD/JZKbdXhITMLUpLS0FAAQEBGDNmjWQ/fVMvb29MW3aNJw6dUpdkZBp6QWlUqlzYgwRERGZj2STCVW1oVevXoJkoUePHgAql4yGhoYCgNYKRFFRETw9PY16bKXS/Hu+5+U9EvxbLrf8nvJiPKapxIrZ1vqK/aTpH/+YqXP2vT4z7wsKSs0aj5T7Shu+pkxj6fOEWLqf/Pw8TKpOSDaZaN68OWQymbpCoaIa25TJZHB3d0dAQACuXbsmOCY7OxsFBQUacymIbI2uXfj02YEPqFvL08y1cRJR7WQAlI9bMlbBJZtMuLu7o0uXLvjmm2/wr3/9S7109MiRIwCAiIgIAJWViqNHj2LOnDnqFR1ff/015HI5unbtKk7wRGag7y58uuYBAHVvFz4ia4iI6IozZ06r21268LtG0unUzJkzcevWLbz22ms4fvw4Pv74YyxatAgxMTFo3749AGDixIm4d+8eJk2ahKNHjyIpKQlLly7F8OHD0aRJE5GfARER2ZvMzPRq7bMiRSIdkq1MAJXVh82bN2P16tWYMmUKPD09ERcXh1mzZqmPCQoKwqZNm7BixQpMnz4dPj4+GDduHKZNmyZi5ESmq20XvtrmAQB1a5iDyFqqv+ccHPgek0wyERsbi9jYWI3LIyIisGPHjhpvGxERgZ07d1oqNCLRcB4AkfQUFxdXaxeJFIl0SHqYg4iIiKRPMpUJqltMWaXA0j2R8bhCiCyByQRZnamrFLhCgcg4XCFkHo0bN0NW1g11u1mzFiJGIw0c5iAiIjLA5MlTBe2JE/8pUiTSwcoEWZ2pqxRYZiUyDlcIkaUwmSBRcJUCkTj43jPd55/vE7S/+mo/+vcfLFI00sBhDpKctWvfQ0JCPD74YJXYoUhaVtYtLF26ALdvZ4kdiuRlZJxDQkI8fvklQ+xQyA6cOfO9oH3q1EmRIpEOJhMkOarJYdnZ90SORNpSUj5BSUkJdu/+ROxQJG/fvsp9aFJSkkWOhMg+MZkgSVm79j1Bm9UJ7bKybuHevbsAgHv37rA6UYOMjHPqEwQqFApWJ4gsgMkESUr1JWusTmiXkiKsRrA6oZuqKqHC6oRu+fl5SEr6EPn5+WKHIml+fg0E7QYNGooUiXQwmSCyQaqqxOP2HZEikT5VVUJXmx5LTT2M69evIjX1sNihSFpBQZ6gXdMmX3UFkwkiG1T9l1CDBgEiRSJ91Zcxclmjdvn5eUhPT4NSqUR6+hlWJ2oQGhperd1JpEikg8kEkQ2Kjf2boP3ii3/TcSQNHTpc0I6NHSFSJNKWmnoYSqUSAKBUKlmdqEFUVDQcHSt3VnB0dERUVLTIEYmPyQSRDWrcuIm6OtGgQQAaNWosckTSFRbWUV2NkMvlCAkJEzkiacrMTBdMVM3MPCtyRNLl6emF8PAukMlkCA+PgKenp9ghiY7JBEkKy/f6i439G1xcXFiV0IOqOsGqhG6hoeGCpIul+5pFRUWjRYuWrEr8hTtgkqTExv4NH374H3WbX5S6NW7cBHPnviN2GDYhLKwjwsI6ih2GpEVFRSM9PQ0AIJPJ+CVZC09PL4wbN1nsMCSDlQmSFJbvyRK4W2jtWLonUzCZIMlh+Z7MjbuF6oelezIWhzlIcli+J3PStlsoK17asXRPxmJlgojsGncLJbI8JhNEZNe4WyiR5TGZICK7xuXGRJbHZIIkhycb0k9GxjkkJMTzLJi14G6hRJbHZIIkhycb0o/qbJg8C2bNuNyYyPKYTJCk8GRD+snIOCfY+pjViZpxuTHZCoVCgZycBxp/Vc9MmpeXq/WYnJwHop0Vl0tDSVK0nWxo0KBhIkclPaqqhEpKSjLPOVEDLjcmW6BQKLBu3Wrk5GTXeFxS0oc6r/Px8cPUqbOsfnZcViZIUniyIf1U//Uh1q8RIiKAlQmSmNDQcJw9ewYKhYInG6qBXC4XJBDW/hVCROYnl8sxdeoswZBGVWvXrlD/e8aMOVqP8fLyFuXzgJUJkpSoqGjIZDIAPNlQTVRnwVTh2TCJ7INcLoePj6/GX0aGcF7U+fOZWo8T64cFkwmSFJ5sSD9hYR0Fp4vmfAki+3b06FeC9jffHBApEu2YTJDk8GRD+lFVJ1iVICKxcc6EGSkUCp1jXdWX9Wgj1liX1PBkQ/oJC+uIsLCOFrlvXa9lvo6F+J7XH19T9o3JhJnou6QH0L2sR6wlPURVmbo8ra68jvme1589vqby8/Owa9fHiIsbaZXh2D59+guGOmJiBlj8MQ3BYQ4iIiIDWXun3qio3oJ2jx5RVnlcfbEyYSa1LekBgIqKCgCAg4P2HI6lPJKC2l7LfB1Xqq2f7t27gx07tqjbI0eO1TjpGPuqkq29pqrv1BsVFW3V6oTUqhIAkwmzUi3pIbJ1fC3rp6Z+2rFjs6D9zTcHMGXKTCtEJU329JoSa6feqKjeGhUKqeAwBxEZZMOGtUhIiMeHH34gdiiSdu/e3WrtOyJFQubGnXo1MZkgIoPcvZsFAMjKuilyJNJWfUijQYMAkSIhcwsNDRfs88KdeplMEJEBNmxYK2izOqFbebnwfCmqeQFk+7hTryYmE0SkN1VVQoXVCd2qL4PMzr4nUiT6y8/PQ1LSh8jPz7fq4yYn70BCQjx27/7Eqo9rLO7Uq4nJBBERAbD+ckeVCxcqzzuRmZlu1cc1BXfqFeJqDjtgys5ygPSWXVkSd+Ej0k6s5Y7JyTsE7d27P8GLL/7N4o9rKu7UK8RkwsaZurMcIM3d5SzBHnfhI+lq2LCxYFioceOmIkZTO7GWO6qqEiqZmek2kUyQEIc5iIgs4J//nCFoT548TaRI9MPljmQKViZsXE07y/3f//0HJSWP1G1XV1dMnjxd47i6Ur63t134SPpU1QmpVyWAyuWOZ8+egUKh4HJHMhiTCTuga2e5qokEADx69MhudqAzVk278KWmHlNvVSu1fe/JNnXpEokDB/YiIqKr2KHUKioqGunpaQCsu9yxXbswwVBHaGi4VR6XzIvDHER/UZ2R75tvDogcCdmLAwf2AgD2798jciS1E2u544gRIwVtzpewTUwmiFBZlajq5MlUcQIhu3H69ClBOy3ttEiR6E+s5Y7t2oUBYFXClnGYgwiPqxIq33xzgEMdWoSFdUFGRpq63bnzUyJGI22qqoTK/v170KVLpEjR6Ees5Y6V1YmRtR5H0sXKBEmOWLvwUe1iY18StIcMeVGkSMiepKYeQ0JCPCuCNozJBEmOWLvwkX58ff0AAH5+/iJHQvaC85VsH5MJO+bo6CRoOzk5ixSJ/qrvwmet6oSzs4ug7eLiapXHtTX5+XnqpbW5uQ9ZParBgAHCDZ8GD35BpEikjfOV7AOTCTtWXl4maJeVlYoUif607cJnDaWlJYJ29WW1VEms/z+2KDKym6At9fkSYtE2X4lsj2SSiQsXLiAkJAS3b9/Wecy7776L9u3ba1yemZmJ0aNHo1OnTujZsydWr16NsrIyLfdAUsdd+KSN/38M07x5SwDAE08EihsIkYVJIpm4fPkyJk+ejPLycp3H/Pjjj9i2bZvG5deuXcPYsWPh4uKCNWvWYPz48UhKSsLSpUstGTJZSGhouHqXSe7CJz38/6O//Pw8ZGXdAADcvPknh4TIromaTJSXl2P79u2Ii4tDSUmJzuOKioowd+5cNGzYUOO6jRs3wtPTExs2bEBUVBTGjx+PuXPn4pNPPsGdO3csGb7kqdZuq9jCGu6oqGjIZDIA1t2Fz9vbR9D28fGzyuPamqioaEFlgqdf1o1DQvrp06e/oB0TM0CkSMgUoiYTaWlpWLlyJcaPH4/Zs2frPG758uXw9/dHbGysxnUnT55Enz594Oz8eHJh//79oVAocOLECYvEbStscWc5sXbhmznz34L2jBlvWOVxbY2np1e1tnX+/9giDgnpJyqqt6DN/V1sk6jJRFBQEA4dOoSpU6fqPIHSyZMnsW/fPixdulTjBEzFxcXIyspCYKBwPNLX1xceHh64cuWKxWK3BWvXvidof/DBKpEiMYxYu/CpqhOsSuhmi7s6ioVDQvpTVSdYlbBdou6A6e9f8zr1/Px8zJs3D9OnT9dIGFTXA4CHh4fGde7u7igoKDAqLpkM8PZ2M+q2UpKTky1oZ2ffs4nn5e3thn/9619Wf9yEhASrP6at0barY9++vcUIRfIGDRqI9PSfACjg4OCAwYMHwstL+u8/MQwZMgBDhjCRENNfo8tGk8QETF3effddNGrUCGPHjtV6vWo8UqalF5RKpc5TSRNps379esycOQMffvhfsUMhO+Dt7Y3IyK6QyWTo2rUrvLy8ar8RkY2S7Lk5jh49ii+++AK7d+9GRUWF+g+onLjp4OCgrkhoq0AUFRUZPZ6rVAK5ucXGBy9h9vq8zOHSpd8AABcvXmQ/GYB9pVu3blG4ceMWunXrzX4iSfPz8zCpOiHZn+5ff/01SkpKMGjQIISEhCAkJAQbNmyAQqFASEgI1q9fD3d3dwQEBODatWuC22ZnZ6OgoEDr0Ehd4uoqLKm6ubmLFIn0bd6cKGh/9NEmkSKRNu7qaBjVibM4UZXsnWQrE1OnTsWoUaMEl+3cuRO7d+9GcnKyeplojx49cPToUcyZM0e9ouPrr7+GXC5H165drR63lDx6JPwlVFxcKFIk0nf16iVBW1WlIKHIyG6CeRPc1ZGIAAknE82aNUOzZs0Elx07dgwAEBoaqr5s4sSJ+OKLLzBp0iSMGTMGV69exerVqzF8+HA0adLEmiET1QkDBgzDgQN7WZUgIjXJJhP6CgoKwqZNm7BixQpMnz4dPj4+GDduHKZNmyZ2aER2KTKym8Z5J4iobpMpVUsiSK2iQonsbOOWlUrJ6dOnBCXpwYNfYFlah82bEwVDHcHBrfHKK+NFjIio7khNPYajR79CTMwAblolEj8/Dzg4GD8DU7ITMMl0PGuh/saOnShoM5Egsh7VmUN5xlDbxWTCjmVl3RK0b9/OEikS29CyZTCAyqoEEVlHauoxQfvkyVRxAiGTcJhDC3sZ5li/fjXu3burbjdoEIApU2aKGBERkVBCQryWy5aJEEndxmEO0qlqIlHZrttnUSUiIstgMmHH6tUTblLl7q55DhMiIiJTMZmwY0VFwk2qCgttf+iGiOxL9XMoOThoP4M0SRuTCSIiEo3qnEuP2wqRIiFTMMj40x0AABKtSURBVJkgIiLRuLq6VmvzNO22iMmEHevTp7+gHRMzQKRIiIi0i4sTnoNp+PBROo4kKWMyYceionoL2txZjoikJjj4SXV1wtXVDa1aBYscERmDyYSdU1UnWJUgIqmKixsFmUzGqoQN46ZVWtjLplVERET64KZVREREJComE0RERGQSJhNERERkEiYTREREZBImE0RERGQSJhNERERkEiYTREREZBImE0RERGQSblqlhVKpBHuFiIjqCpkMkMmM37SKyQQRERGZhMMcREREZBImE0RERGQSJhNERERkEiYTREREZBImE0RERGQSJhNERERkEiYTREREZBImE0RERGQSJhNERERkEiYTREREZBImE0RERGQSJhNERERkEiYTVnbu3Dm8/vrriIqKQlhYGGJiYrBw4ULcuXNHfUx8fDxiYmJ03kffvn0xb948dXv06NEICQnBhQsXtB7fvn17fPDBB+Z7EhY2evRojB07Vuf11Z/PmTNn8NprryEyMhIdOnRA79698eabb+LPP//UeR/Tpk1DmzZtkJycbM7QrS4+Ph5t2rTR+ffdd99h9OjRGpe3bdsWnTt3RmxsLPbt26fz/mNjY9GmTRucOHHCis/K8j744AO0b98eN27cqLH/VH+nT58W3D47OxsdOnRAp06dUFBQINKzsCx9Pquqqu09ZW+fUyq///47FixYgJiYGHTs2BFPPfUURo8ejb1796LqeTRre41t3LgRAHS+Jjt06IAePXpg6tSpuHLlilhPVydHsQOoS7Zs2YLly5eje/fueOONN9CgQQP88ccfSExMxMGDB/HRRx+hZcuWRt13eXk53nzzTXz66adwdKw7/1tPnDiBSZMmoX///liyZAk8PT1x/fp1JCYmIi4uDp9++ilatGghuM2DBw9w9OhRtG7dGsnJyRgxYoRI0ZtHo0aNsHbtWq3XBQcHAwBCQ0Mxf/589eUVFRW4ffs2tmzZgjlz5qB+/fqIiooS3PbixYv45Zdf1P3Us2dPyz0JkTRs2FDw5ffLL79g4cKFWLhwIdq0aaO+XNWPKp999hkCAgLw4MEDfPbZZxg5cqTVYrYGQz+r9H1P2dvn1P79+zFv3jy0bt0akyZNwhNPPIGCggIcOnQIc+fOxdmzZ/HOO++ojx8xYgRiY2O13lfjxo0F7WnTpgnec48ePcL58+fx3//+F+PHj8dXX30FFxcXyzwxI9j+/00bkZaWhmXLlmHMmDGIj49XXx4ZGYno6GgMHToUCQkJ2Lx5s1H37+npifPnz+P//b//h3/84x9milr6Nm7ciM6dO2P16tXqyyIjI9GrVy/ExMQgKSkJCxYsENxm//79cHFxwezZszFp0iRkZmYiNDTU2qGbjbOzM8LDw2s8xsPDQ+sxvXr1wtNPP42UlBSNZCIlJQXBwcH4+9//joSEBNy9excNGzY0a+xiq953JSUlAICgoKAa+zQlJQV9+vRBdnY2kpOT7SqZMOazSt/3lD19Tv3xxx+YN28eevfujffffx9yuVx9Xd++fdG+fXssWrQIQ4cORefOnQFUJv61vVdVmjdvrnFst27dUK9ePSxYsACnTp3SeM+KicMcVvK///0P9evXx8yZMzWuCwgIQHx8PJ5++mmUl5cbdf8dOnTAwIEDsWHDBvzxxx+mhmszsrOzUVFRoXF5QEAA3nrrLfTo0UPjupSUFPTo0QPPPPOMxi/TusbZ2RlOTk6QyWSCy8vKyrB//3706tULzz33HORyOXbv3i1SlNKSmZmJ3377DVFRURgyZAguXryIc+fOiR2W2RjzWaXve8qePqcSExMhl8uRkJAgSCRUXn75ZcTExODRo0dmfVxPT0+z3p+5MJmwAqVSiRMnTuDpp5/WWZYaNmwYJk+eLCj9lZeXa/3TZf78+XB3d8ebb76p9QvWHvXq1QtpaWkYM2YMUlJSBPMkXnrpJfTr109w/IULF3Dx4kUMHToUDg4OGDp0KL744gubH/fW9jqpOl6rVCoF15WUlOCPP/7A3LlzUVhYiKFDhwru79ixY3jw4AGGDh0KLy8vREdH49NPP60zr6uapKSkoEGDBujevTueeeYZNGjQAJ988onYYZmFMZ9Vhr6n7OVz6vDhw+jWrRt8fX21Xi+Xy7Fu3Tp0795dfVlFRYXen+vV37P5+fk4ceIEVq1ahaZNmyIiIsJiz80YTCasICcnByUlJWjSpInet7l+/TpCQkK0/t28eVPrbXx9ffHWW28hPT0dW7ZsMVf4kjZz5kwMHz4cZ86cwdy5c9GvXz9ERUXh7bffxuXLlzWO3717N/z8/NTlwdjYWBQVFeGzzz6zduhmo+u1UvUL7tSpU4LrwsLCMHDgQFy6dAlr165Fnz59BPe5e/dutG/fHm3btgVQ2U83b97E8ePHrfrcpKa0tBRffPEFhgwZArlcDkdHRwwePBgHDhxAXl6e2OGZzJjPKkPfU/bwOZWbm4vc3Fytc9yqJwkKhUJ93QcffKDzc101xKby73//W3B9REQEpk2bhpCQEGzZsgXu7u6WfpoG4ZwJK1CVwKq+qGrTqFEjrFu3Tut1NY01Dhw4EJ9//jnWrl2L6OhojcmH9kJVlnd2dsaiRYswY8YMpKam4vvvv8fp06eRnJyMlJQUrFmzRl2dKC0txf79+9G/f38UFRUBAPz9/RESEmLT4966XitNmzZV/zssLAxvv/02AODOnTtYu3YtysvL8f7776NVq1aC292/fx/Hjx/H9OnT1V+QoaGh8Pf3R3JysqTGaa3t0KFDyM3NRb9+/dR9ExMTg02bNuGzzz7DK6+8InKEpjH0s8rY95Stf07pqqhkZmYiLi5OcFnXrl2xbds2AJVDHy+++KLW2zo7Owva06dPR69evaBUKvHjjz9izZo1GDRoEBYsWCDJyavSi8gOeXt7w93dHbdu3dJ5jKok6OHhAaDyhaVrUmD1F111CQkJGDRoEObNm4etW7caGbV46tWrh/z8fK3XVVRUQKFQwM3NTXC5v78/XnzxRfUb9fTp05g9ezYSEhIQHR0NmUyGI0eO4OHDh/jkk0+0lqXPnTuHjh07mv8JWVhNrxUVd3d39TGhoaEIDw/HkCFDMGHCBOzevVtQqt23bx/Ky8uxevVqwcRWoHL4486dOwgICDD/E7EBqnkjL7/8ssZ1ycnJNp9MGPpZZcp7ypY/p3x8fFCvXj2NfgoODsauXbvU7YULFwqub9iwod6TvZs1a6Y+NiwsDD4+Ppg7d656nobUcJjDSnr27InTp09rlLJUNm/ejK5du+LatWsmP1ZAQAD+/e9/44cffsDHH39s8v1Zm7+/P+7evav1utu3b6uPOXfuHLp3746TJ09qHBcZGYkJEybg3r17yM3NBVA51t2yZUts3bpV8Ldp0yY4Ozvbzbi3Pvz9/fH222/j1q1bWLJkieC6PXv2ICIiQqOf1qxZA4VCgU8//VSkqMV1584dfPfddxgzZoxG37z66qv47bff8NNPP4kdpskM+awy5T1l659Tffv2xYkTJ9QVGQBwc3NDaGio+s+cQxGxsbHo3bs3Pv74Y0nu+8JkwkrGjRuHhw8fat0P4NatW9i+fTvCwsLwxBNPmOXx4uLi0KNHD6xcudLmJjl17doVf/75JzIzMzWuO3jwIBwcHPDUU0+hZcuWKCoqwtatW7U+xytXriAgIAD169fH3bt3ceLECQwcOBCRkZGCvx49eqBPnz52M+6tr/79++OZZ57B559/jh9++AEAkJGRgd9//x2xsbEa/TRgwAB06NABu3btMmjIzl7s2bMHSqUSY8eO1eib8ePHw8nJyS5WBun7WeXm5mbye8qWP6deffVVlJaW4q233kJZWZnG9Xl5eTo3+DLWW2+9BRcXFyxatEjrY4qJyYSVdOrUCVOmTMH//vc/vPbaazhw4AC+//57JCUlYfjw4XBwcMB7771n1sdctGgRlEqlYFa/LXj++ecREhKCSZMmYfPmzTh9+jQOHTqExYsXY+XKlRg3bhyaNGkCb29vvPHGGzh27BhGjhyJlJQU/Pjjjzhy5Ajmzp2LnTt3Yu7cuQCAvXv3QqFQYODAgVofc9iwYSguLrbpiZjGePPNN+Hk5ITFixdDoVBg9+7dcHZ2xrPPPqv1+GHDhiErKwvffvutlSMV3549e9CpUyetkxN9fX3xzDPP4MCBA+pKmK3S97PKXO8pW/2catu2LVasWIEjR47gxRdfxLZt23Dq1CmkpqbivffeQ0xMDG7evInnnntOfZvbt28jPT1d658+S2WbNWuGCRMm4OrVq5KbvMo5E1akmom7fft2LFmyBHl5eWjcuDH69++PSZMmmX1DoKZNm+L111/HokWLzHq/lubk5IRt27bhv//9Lz7++GPcvn0bTk5OCAwMxDvvvCOYwDRq1Ci0atUKW7duxerVq/Hw4UO4u7vj/7d3fyFNf38cx1/TlmWEIhqFFf0hJlKWGYkXdRH9g5i1JWSQA2UW8yaIwoqK1UUiIYsSIalZF64WUgt1dGNBSF1URFgMCmqRXeT6YyTRxsZ+F+FAbNm3ze+v+j4fl+ec92c7F3724nP8nFNSUqJLly5p9erVkr79EBQVFWnx4sXf/cy1a9cqLy/vr1j3/icWLVqkmpoaud1uXb58WX6/X2vWrEn6LvuWLVvU3NysK1eujHsD5G/24MEDBYNB1dTUJB2zbds23bp1S9evX//hdvB/gp+5V6Xrb+pPvU9JSjyt6+zslMfjSSzDLly4UNXV1dq5c6dmz56dGO/1epM+vaqoqPipTQv37Nkjn8+ntrY2VVZW/jYbyRnif1ocBAAAvxWWOQAAQEoIEwAAICWECQAAkBLCBAAASAlhAgAApIQwAQAAUkKYAJCygwcPymQyqbOz87v9g4ODMplMOnv27Jj2SCSijo4OVVVVaeXKlSorK5PFYtH58+eTns8ifTsfwu12y2q1qqysTCtWrFBVVZW8Xu8ft5Mi8Ddg0yoAaeNyubRp0ybl5+dPOPbt27ey2+16/vy51q9fL4vFong8rkePHsnlcsnr9ercuXPjTjV98eKFHA6H3rx5I7PZrO3btyscDquvr0/Hjh3T/fv3derUqcTJsgAmH2ECQNp8/vxZTU1Namlp+eG4SCQih8OhwcFBdXR0qKKiItG3a9cu2Ww27d69W/X19erp6UmcEhsOh9XQ0KDh4WF1dXWpqKgoUVdXV6fjx4/L4/GopKRENpttciYJYByWOQCkzbp169TT06N79+79cJzP59PTp0/V2Ng4JkiMWr58uQ4fPqzBwUFduHAh0e7xePTy5UsdOnRoTJAY1djYqJycnP/UCbDA74AwASBtjhw5ounTp8vpdCoSiSQd5/P5lJ2dLYvFknRMZWWlCgoK1N3dnWjr7e1VdnZ20sOlpk2bpqtXr8rn8/36JAD8Y4QJAGlTWFiohoYGBYNBtbe3f3dMLBbTwMCAiouLlZWVlfRaBoNB5eXlCgaDCoVCisfjCgQCWrp0qYxGY9K6BQsWaOrUqSnPBcDPI0wASKva2lotWbJE7e3tevXq1bj+T58+KRKJqKCgYMJrjZ6IODQ0pI8fPyoajf5UHYB/F2ECQFoZjcbEMseJEyfG9Y8eVJyZmTnhtaZMmZKoycj4druKxWJp/LYA0oEwASDtVq1aJYvFov7+fvX29o7py8vLk9Fo1Pv37ye8ztDQkKRvTyhycnJkNBr14cOHSfnOAH4dYQLApDhw4IByc3PV1NSkkZGRRLvBYFBpaakGBgYUDoeT1sfjcT18+FDz5s3TrFmzEnVPnjxRNBpNWudyubRv3z6FQqG0zgdAcoQJAJMiLy9P+/fvVygU0unTp8f0bd26VSMjI/J6vUnr+/r69Pr1a5nN5kTbhg0b9OXLF/n9/u/WfP36VV1dXbp7965yc3PTMxEAEyJMAJg0o9tk3759e0y71WpVaWmpWlpa1N/fP64uEAjo6NGjmjt3rux2e6J9x44dKiwsVHNzs549ezamJhaLyel06t27d6qvr//hGx8A0osdMAFMGoPBIKfTKavVOmZpIiMjQ62trXI4HLLb7dq4caPKy8uVmZmpx48fq7u7W3PmzFFbW5tmzJiRqMvKylJra6vq6upUVVUls9msZcuWaXh4WDdv3lQgENDmzZtVW1v7/5gu8J9FmAAwqUwmk2w2m9xu95j2/Px8dXZ2yufz6dq1azpz5oyi0ajmz5+vvXv3qrq6WjNnzhx3veLiYt24cUMXL17UnTt35Pf7FY/HZTKZdPLkSVmtVs7lAP5lhvjoe1oAAAC/gP+ZAAAAKSFMAACAlBAmAABASggTAAAgJYQJAACQEsIEAABICWECAACkhDABAABSQpgAAAApIUwAAICU/A+Md64Exw4PlQAAAABJRU5ErkJggg==\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(\n",
    "    x='NOC',\n",
    "    y='Height',\n",
    "    hue='Sex',\n",
    "    data=df\n",
    ")\n",
    "plt.legend(loc='upper right')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x25180ec0be0>"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 9
    },
    {
     "data": {
      "text/plain": "<Figure size 576x432 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(\n",
    "    x='Height',\n",
    "    y='NOC',\n",
    "    hue='Sex',\n",
    "    data=df\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x25180fe6208>"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 10
    },
    {
     "data": {
      "text/plain": "<Figure size 576x432 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(\n",
    "    data=df[['Height', 'Weight', 'NOC']]\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "language": "python",
   "display_name": "Python 3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "3.7.6-final"
  },
  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
    "source": [],
    "metadata": {
     "collapsed": false
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}